估算的总冠层SIF排放对遥感LAI和BRDF产品的敏感性

遥感学报 Pub Date : 2021-09-17 DOI:10.34133/2021/9795837

Zhaoying Zhang, Yongguang Zhang, Jing M. Chen, W. Ju, M. Migliavacca, T. El-Madany

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引用次数: 19

摘要

太阳诱导叶绿素荧光(SIF)遥感为估算陆地初级生产总量(GPP)提供了新的可能性。为了减轻角度和冠层结构对传感器观测到的原始SIF的影响，建议使用冠层拦截(i0)和植被反射率(RV)来计算冠层内叶片的总SIF发射(SIFtotal)。然而，i0和RV的不确定性对SIFtotal估计的影响尚未得到很好的理解。本文利用土壤-冠层-光合作用观测和能量平衡(SCOPE)模型评估了这种影响对GPP估算的影响。SCOPE模拟结果表明，GPP与SIFtotal之间的R2明显高于GPP与SIFobs之间的R2，且R2 (ΔR2)的差异随着i0和RV不确定性水平的增加而减小。当红外波段SIF (RSIF, 683nm)和远红外波段SIF (FRSIF, 740 nm)的不确定度分别为~30%和~20%时，所得ΔR2降至零。此外，与对流层监测仪器(TROPOMI)在红色和远红色波段的sifbs相比，使用i0(来自MCD15、VNP15和CGLS LAI产品)和RV(来自MCD34、MCD19和VNP43 BRDF产品)的任何组合获得的SIFtotal在估计GPP方面都显示出相当的改善。通过这项研究，我们提出了一种方法来提高我们对使用当前卫星产品估计更生理相关的SIF数据集(SIFtotal)的理解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Sensitivity of Estimated Total Canopy SIF Emission to Remotely Sensed LAI and BRDF Products

Remote sensing of solar-induced chlorophyll fluorescence (SIF) provides new possibilities to estimate terrestrial gross primary production (GPP). To mitigate the angular and canopy structural effects on original SIF observed by sensors (SIFobs), it is recommended to derive total canopy SIF emission (SIFtotal) of leaves within a canopy using canopy interception (i0) and reflectance of vegetation (RV). However, the effects of the uncertainties in i0 and RV on the estimation of SIFtotal have not been well understood. Here, we evaluated such effects on the estimation of GPP using the Soil-Canopy-Observation of Photosynthesis and the Energy balance (SCOPE) model. The SCOPE simulations showed that the R2 between GPP and SIFtotal was clearly higher than that between GPP and SIFobs and the differences in R2 (ΔR2) tend to decrease with the increasing levels of uncertainties in i0 and RV. The resultant ΔR2 decreased to zero when the uncertainty level in i0 and RV was ~30% for red band SIF (RSIF, 683 nm) and ~20% for far-red band SIF (FRSIF, 740 nm). In addition, as compared to the TROPOspheric Monitoring Instrument (TROPOMI) SIFobs at both red and far-red bands, SIFtotal derived using any combination of i0 (from MCD15, VNP15, and CGLS LAI products) and RV (from MCD34, MCD19, and VNP43 BRDF products) showed comparable improvements in estimating GPP. With this study, we suggest a way to advance our understanding in the estimation of a more physiological relevant SIF datasets (SIFtotal) using current satellite products.

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来源期刊

遥感学报 Social Sciences-Geography, Planning and Development

CiteScore

3.60

自引率

0.00%

发文量

3200

期刊介绍： The predecessor of Journal of Remote Sensing is Remote Sensing of Environment, which was founded in 1986. It was born in the beginning of China's remote sensing career and is the first remote sensing journal that has grown up with the development of China's remote sensing career. Since its inception, the Journal of Remote Sensing has published a large number of the latest scientific research results in China and the results of nationally-supported research projects in the light of the priorities and needs of China's remote sensing endeavours at different times, playing a great role in the development of remote sensing science and technology and the cultivation of talents in China, and becoming the most influential academic journal in the field of remote sensing and geographic information science in China. As the only national comprehensive academic journal in the field of remote sensing in China, Journal of Remote Sensing is dedicated to reporting the research reports, stage-by-stage research briefs and high-level reviews in the field of remote sensing and its related disciplines with international and domestic advanced level. It focuses on new concepts, results and progress in this field. It covers the basic theories of remote sensing, the development of remote sensing technology and the application of remote sensing in the fields of agriculture, forestry, hydrology, geology, mining, oceanography, mapping and other resource and environmental fields as well as in disaster monitoring, research on geographic information systems (GIS), and the integration of remote sensing with GIS and the Global Navigation Satellite System (GNSS) and its applications.